class_docstr: Naive preprocessor.
  
  Example:
      >>> import matchzoo as mz
      >>> train_data = mz.datasets.toy.load_data()
      >>> test_data = mz.datasets.toy.load_data(stage='test')
      >>> preprocessor = mz.preprocessors.NaivePreprocessor()
      >>> train_data_processed = preprocessor.fit_transform(train_data,
      ...                                                   verbose=0)
      >>> type(train_data_processed)
      <class 'matchzoo.data_pack.data_pack.DataPack'>
      >>> test_data_transformed = preprocessor.transform(test_data,
      ...                                                verbose=0)
      >>> type(test_data_transformed)
      <class 'matchzoo.data_pack.data_pack.DataPack'>
docstr: Apply transformation on data, create `tri-letter` representation.
  
  :param data_pack: Inputs to be preprocessed.
  :param verbose: Verbosity.
  
  :return: Transformed data as :class:`DataPack` object.
docstr_tok: ["Apply","transformation","on","data",",","create","`","tri-letter","`","representation",".",":","param","data_pack",":","Inputs","to","be","preprocessed",".",":","param","verbose",":","Verbosity",".",":","return",":","Transformed","data","as",":","class",":","`","DataPack","`","object","."]
code: def transform(
      self, data_pack: DataPack, verbose: int = 1
  ) -> DataPack:
      """
      Apply transformation on data, create `tri-letter` representation.
  
      :param data_pack: Inputs to be preprocessed.
      :param verbose: Verbosity.
  
      :return: Transformed data as :class:`DataPack` object.
      """
      units_ = self._default_units()
      units_.append(self._context["vocab_unit"])
      units_.append(units.FixedLength(text_length=30, pad_mode="post"))
      func = chain_transform(units_)
      return data_pack.apply_on_text(func, verbose=verbose)
  
file_path: MatchZoo/matchzoo/preprocessors/naive_preprocessor.py
imports: from tqdm import tqdm
  from matchzoo.engine.base_preprocessor import BasePreprocessor
  from matchzoo import DataPack
  from .chain_transform import chain_transform
  from .build_vocab_unit import build_vocab_unit
  from .None import units
label_desc: Use image node_id 2 for calling the NaivePreprocessor obj's underlying member method code with example usage: obj.transform(data_pack, verbose) and returns: data_pack